Ahmed Elazab

09/2012-01/2017, University of Chinese Academy of Sciences, Pattern Recognition & Intelligent Systems, PhD

09/2001 - 07/2005, Mansoura University (Egypt), Computer Science, Master

09/2001 - 07/2005, Mansoura University (Egypt), Computer Science, Bachelor

08/2017 -04/2020, Postdoctoral Fellow, Shenzhen University

01/2021 -12/2024, Associate Researcher, Shenzhen University

04/2025 -10/2025, Associate Researcher, Shenzhen University of information Technology 

11/2025 – now Assistant Professor, Tsinghua SIGS

1. PeerJ Computer Science, PeerJ Publisher, Academic Editor (June 2020 till now)

2. Neuroscience Informatics, Elsevier, Deputy Editor, (Oct 2021 till now).

3. Frontiers in Neuroscience, Frontiers, Associate Editor (Feb 2022 till now). 

4. Frontiers in Neuroimaging, Frontiers, Associate Editor (Feb 2022 till now).

My research focuses on developing trustworthy artificial intelligence for medical image analysis, with a special emphasis on brain disease diagnosis and prognosis. I integrate advanced machine and deep learning techniques with multi-modal neuroimaging data fusion to build robust computer-aided detection and diagnosis systems. A core aspect of my work involves applying pattern recognition and neural informatics to uncover disease-specific biomarkers, while simultaneously prioritizing explainable AI to ensure clinical interpretability and trust. Ultimately, my goal is to create reliable decision-support tools that can be integrated into clinical workflows for improved neurological care.

1- “Advancing Artificial Intelligence Research on Brain Diseases Diagnosis and Detection”, Shenzhen Municipality after postdoc funding, 2021-01 to 2024-12, principal investigator (300,000 RMB)

2- “Joint Growth and Survival Time Predictions of Glioma Using Stacked Generative Adversarial Networks”, Research Fund for International Young Scientists, Natural Science Foundation of China, 2020-01 to 2021-12, principal investigator (200,000 RMB)

1- M. Abdelaziz, T. Wang, W. Anwaar, A. Elazab*.  Robust attention transfer neural networks for diagnosis of Alzheimer's disease from structural magnetic resonance images, Engineering Applications of Artificial Intelligence, 164, 113260, 2026 (IF= 8.0, Q1).

2- A. Elazab, H. Wang, C. Wang, Y. Zhang, J. M Gorriz, J. Cai, C. Chang*.  Improved Alzheimer’s disease diagnosis using multimodal sparse similarity feature selection and auxiliary data, Biomedical Signal Processing and Control, 112, 108485, 2026 (IF= 4.9, Q1).

3- X. Yu#, A. Elazab#, R. Ge, J. Zhu, L. Zhang, G. Jia, Q. Wu, X. Wan, L. Li, and C. Wang. ICH-PRNet: A cross-modal intracerebral haemorrhage prognostic prediction method using joint-attention interaction mechanism, Neural Networks, 184, 107096, 2025 (IF= 6.0, Q1).

4- A. Elazab, C. Wang, M. Abdelaziz, J. Zhang, J. Gu, J. Gorriz, Y. Zhang, C. Chang*.  Alzheimer’s disease diagnosis from single and multimodal data using machine and deep learning models: Achievements and future directions. Expert Systems with Applications, vol. 255, 124780, 2024. (IF= 7.5, Q1).

5- A. Elazab, M. AbdElfattah. Y. Zhang*.  Novel Multi-Site Graph Convolutional Network with Supervision Mechanism for COVID-19 Diagnosis from X-ray Radiographs. Applied Soft Computing, vol. 114, 108041, Jan 2022. (IF = 6.725, Q1).

6- A. Elazab, C. Wang, S. J. S. Gardezi, H. Bai, Q. Hu, T. Wang, C. Chang*, B. Lei*.  GP-GAN: Brain Tumor Growth Prediction Using Stacked 3D Generative Adversarial Networks. Neural Networks, vol. 132, pp. 321-332, 2020 (IF= 5.535, Q1).

7- C. Fan#, A. Elazab#, S. Zhang, Y. Wang, Q. Liang, D. Li, Y. Zhang, Y. Xiang, B. Liu, C. Wang*. Clinical Prior Guided Cross-Modal Hierarchical Fusion for Histological Subtyping of Lung Cancer in CT Scans. International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 75-84. Springer, 2025.

8- J. Yu, R. Ge, Z. Wang, C. Yang, C. Lin, X. Fu, J. Liu, A. Elazab*, C. Wang*. “Small Lesions-aware Bidirectional Multimodal Multiscale Fusion Network for Lung Disease Classification. International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 589-598. Springer, 2025.

9- X. Yu#, A. Elazab#, R. Ge, H. Jin, X. Jiang, G. Jia, Q. Wu, Q. Shi, C. Wang ICH-SCNet: Intracerebral Hemorrhage Segmentation and Prognosis Classification Network Using CLIP-guided SAM mechanism. 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Lisbon, Portugal, 2024, pp. 2795 - 2800.

1. Best paper award of the 2023 International Workshop on Computational Mathematics Modeling in Cancer Analysis, MICCAI (co-author).

2. The only nominee among all international students from University Chinese Academy of Sciences to attend and present in the International Student Research Forum (ISRF) 2016.

3. Outstanding student award from the Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences 2014 and 2015.

4. Best paper award of the IEEE/EMB Cairo International Biomedical Engineering Conference, 2014 (1^st author).